Addressing emerging contaminant: The role of nano‐filtration in removing methylparaben from wastewater
Bibliographic record
Abstract
Abstract Methylparaben, commonly found as an emerging contaminant in personal care products and pharmaceuticals, have raised concerns due to their potential endocrine‐disrupting effects on humans and male fish. Nano‐filtration presents a viable alternative for mitigating this contamination. In this paper, the first part explores advances in various methods, each of which facilitates the separation of paraben from aqueous media. In the later experimental segment, the flat sheet membrane module is used for nano‐filtration, for different operating parameters. The two NF300 & NF100 membranes are employed to see the efficiency of removal of nethylparaben from synthetic wastewater. The removal efficiency of methylparaben by NF300 membrane is 32.64%, while the removal efficiency by NF100 membrane is 70.46%. The efficiency of the membrane increases with the increase in pressure and decrease in the concentration. The outcome shows nano‐filtration is a promising technology for addressing the emerging contaminant methylparaben in waste water.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".